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IEEE and Google Team Up to Deliver Tools for Researchers

Hacker News

IEEE and Google Team Up to Deliver Tools for Researchers

We got shown this tonight- https://vimeo.com/71643339 Password: ieee Apps for managing papers have shown up before on HN. This one is available in beta to certain commitees. If you are a member ask others in your society and they may have more info. Skip through his slides. The demo starts halfway through. Many questioned whether this would work for otyer sites like Springer. They didn't know tonight but more info will be released at IEEE Sections Congress this year.

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, apps · Missing: mac, agents, macos
68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: apps, google, way · Missing: mobile apps, ios, personal
62%62% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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